Simona Liao

@simonaliao.bsky.social

84 Followers 9 Following

She/They UW CSE Master Graduate on Human Computer Interaction Product Manager @ Microsoft

Pie chart representing the racial groups, with count in brackets 51.4% White/Caucasian (127) 17.8% Asian (44) 8.9% Prefer not to disclose (22) 8.1% Prefer to self-describe (20) 8.1% Hispanic and Latino (20) 3.6% Black or African American (9) 2.0% Middle Eastern (5)
Figure 4: A collection of 36 heatmaps. The y-axis or each row represents a demographic breakdown (from top to bottom: Race, Gender, Langauge, Experience, Field of Study, and All participants). Each column, from left to right, represents LLM usage frequency, perception of risk, benefits, ethics, the comfort level of disclosing to peers, and of disclosing to reviewers. For each individual heatmap, the x-axis includes the six types of LLM usage (from left to right, information seeking, editing, ideation & framing, direct writing, data cleaning & analysis, and data generation.).
Fig 2: Overview of Usage Frequency Divided by LLM Usage Type (N=816). The left diverging bar chart displays the distribution of usage frequency across different types of LLM usage, with each type represented by a separate row. The frequency levels, from left to right, are: Very Rarely, Rarely, Occasionally, Frequently, and Very Frequently, with the midpoint of the chart centered at "Occasionally." The grey bar chart on the right indicates the percentage of responses that report "Never" using LLMs for each corresponding type. From this plot, we can tell that researchers report using LLMs for Information Seeking and Editing most frequently, and for Data Cleaning & Analysis and Data Generation the least frequently.